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A Big Data framework for actionable information to manage drinking water quality
Water utilities collect vast amounts of data, but they are stored and utilised in silos. Machine learning (ML) techniques offer the potential to gain deeper insight from such data. We set out a Big Data framework that for the first time enables a structured approach to systematically progress through data storage, integration, analysis, and visualisation, with applications shown for drinking water quality. A novel process for the selection of the appropriate ML method, driven by the insight required and the available data, is presented. Case studies for a water utility supplying 5.5 million people validate the framework and provide examples of its use to derive actionable information from data to help ensure the delivery of safe drinking water. HIGHLIGHTS A four-layer Big Data framework for better water quality management is proposed.; Framework consists of data collection, integration, analysis, and visualisation.; Machine learning method selection tool driven by data availability is included.; Framework yields information for interventions to manage drinking water quality.; Two case studies demonstrate the success of the framework.;
A Big Data framework for actionable information to manage drinking water quality
Water utilities collect vast amounts of data, but they are stored and utilised in silos. Machine learning (ML) techniques offer the potential to gain deeper insight from such data. We set out a Big Data framework that for the first time enables a structured approach to systematically progress through data storage, integration, analysis, and visualisation, with applications shown for drinking water quality. A novel process for the selection of the appropriate ML method, driven by the insight required and the available data, is presented. Case studies for a water utility supplying 5.5 million people validate the framework and provide examples of its use to derive actionable information from data to help ensure the delivery of safe drinking water. HIGHLIGHTS A four-layer Big Data framework for better water quality management is proposed.; Framework consists of data collection, integration, analysis, and visualisation.; Machine learning method selection tool driven by data availability is included.; Framework yields information for interventions to manage drinking water quality.; Two case studies demonstrate the success of the framework.;
A Big Data framework for actionable information to manage drinking water quality
Grigorios Kyritsakas (author) / Joseph B. Boxall (author) / Vanessa L. Speight (author)
2023
Article (Journal)
Electronic Resource
Unknown
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